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Genetic Analysis Of Dynamic Root Traits Using Wheat Diversity Panels

Authors: Collet, Clothilde; Thaon, Patrick; Chenue, Karine; Christopher, Jack; Draye, Xavier;

Genetic Analysis Of Dynamic Root Traits Using Wheat Diversity Panels

Abstract

Understanding drought tolerance mechanisms has never been so relevant, especially in view of the increasing diversity of water limited scenarios predicted by climate research. Classically, breeders target above ground traits to improve drought tolerance and a rather limited interest has been given to the root system architecture. Root traits should be considered because roots are key players of soil water extraction. In particular, special attention should be devoted to dynamic root traits in order to shift the focus towards a better understanding of drought resilience. Using time-lapse image sequences of whole root systems over three weeks, we captured dynamic information on root architecture of wheat seedlings growing in aeroponics. Three wheat diversity panels have been phenotyped: a MR-NAM bread wheat population (521 lines), a bread wheat diversity panel (250 varieties) and a durum wheat diversity panel (250 varieties). Data extraction, based on the identification and tracking of root tips in image sequences, has allowed the determination of the root growth rate, emergence, maximum length and apical diameter of primary and seminal roots. For the MR-NAM panel, a high heritability of seminal root emergence has been estimated, despite important environmental and genotype by environment variances. However, for the others seminal traits, heritability tended to be low. Efforts are ongoing to analyse lateral root traits, yet their extraction from images is challenging due the high density of lateral roots. A genome wide association study (GWAS) has been carried out with the MR-NAM population data and has led to the identification of three QTLs, related to seminal root growth rate and maximum root length. Phenotyping of the other panels are still ongoing and a meta-analysis will be conducted using GWAS results from the three panels. These experiments are part of the EU project SolACE (http://www.solace-eu.net). References: Burton, Amy L., James Johnson, Jillian Foerster, Meredith T. Hanlon, Shawn M. Kaeppler, Jonathan P. Lynch, et Kathleen M. Brown. 2015. « QTL Mapping and Phenotypic Variation of Root Anatomical Traits in Maize (<Emphasis Type="Italic">Zea Mays</Emphasis> L.) ». Theoretical and Applied Genetics 128 (1): 93-106. https://doi.org/10.1007/s00122-014-2414-8. de Dorlodot, S., 2007. Root system architecture: a genetic analysis in rice (PhD Thesis). Université catholique de Louvain. de Dorlodot, S., Forster, B., Pagès, L., Price, A., Tuberosa, R., Draye, X., 2007. Root system architecture: opportunities and constraints for genetic improvement of crops. Trends in Plant Science 12, 474–481. https://doi.org/10.1016/j.tplants.2007.08.012 Lynch, J. 1995. « Root Architecture and Plant Productivity ». Plant Physiology 109 (1): 7-13. https://doi.org/10.1104/pp.109.1.7. Thaon, P., 2017. Genetic analysis of wheat root architecture in aeroponics. Tuberosa, R., Sanguineti, M.C., Landi, P., Michela Giuliani, M., Salvi, S., Conti, S., 2002. Identification of QTLs for root characteristics in maize grown in hydroponics and analysis of their overlap with QTLs for grain yield in the field at two water regimes. Plant Mol Biol 48, 697–712. https://doi.org/10.1023/A:1014897607670 Wasson, A. P., R. A. Richards, R. Chatrath, S. C. Misra, S. V. Sai Prasad, G. J. Rebetzke, J. A. Kirkegaard, J. Christopher, et M. Watt. 2012. « Traits and selection strategies to improve root systems and water uptake in water-limited wheat crops ». Journal of Experimental Botany 63 (9): 3485-98. https://doi.org/10.1093/jxb/ers111. Welcker, C., Sadok, W., Dignat, G., Renault, M., Salvi, S., Charcosset, A., Tardieu, F., 2011. A Common Genetic Determinism for Sensitivities to Soil Water Deficit and Evaporative Demand: Meta-Analysis of Quantitative Trait Loci and Introgression Lines of Maize. Plant Physiology 157, 718–729. https://doi.org/10.1104/pp.111.176479

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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